Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector

Manisha Goswami; Supriya Jain; Tabish Alam; Ahmed Farouk Deifalla; Adham E Ragab; Rohit Khargotra

doi:10.3389/fphar.2023.1215706

Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector

Front Pharmacol. 2023 Nov 14:14:1215706. doi: 10.3389/fphar.2023.1215706. eCollection 2023.

Authors

Manisha Goswami¹, Supriya Jain¹, Tabish Alam², Ahmed Farouk Deifalla³, Adham E Ragab⁴, Rohit Khargotra⁵

Affiliations

¹ Institute of Business Management, GLA University, Mathura, India.
² CSIR-Central Building Research Institute, Roorkee, India.
³ Structure Engineering and Construction Management, Future University, New Cairo, Egypt.
⁴ Department of Industrial Engineering, College of Engineering, King Saud University, Riyadh, Saudi Arabia.
⁵ Institute of Materials Engineering, Faculty of Engineering, University of Pannonia, Veszprém, Hungary.

Abstract

Purpose: The aim of this research is to investigate the factors that facilitate the adoption of artificial intelligence (AI) in order to establish effective human resource management (HRM) practices within the Indian pharmaceutical sector. Design/methodology/approach: A model explaining the antecedents of AI adoption for building effective HRM practices in the Indian pharmaceutical sector is proposed in this study. The proposed model is based on task-technology fit theory. To test the model, a two-step procedure, known as partial least squares structural equational modeling (PLS-SEM), was used. To collect data, 160 HRM employees from pharmacy firms from pan India were approached. Only senior and specialized HRM positions were sought. Findings: An examination of the relevant literature reveals factors such as how prepared an organization is, how people perceive the benefits, and how technological readiness influences AI adoption. As a result, HR systems may become more efficient. The PLS-SEM data support all the mediation hypothesized by proving both full and partial mediation, demonstrating the accuracy of the proposed model. Originality: There has been little prior research on the topic; this study adds a great deal to our understanding of what motivates human resource departments to adopt AI in the pharmaceutical companies of India. Furthermore, AI-related recommendations are made available to HRM based on the results of a statistical analysis.

Keywords: artificial intelligence adoption; competitive pressure; human resource management effectiveness; organization preparedness; organizational culture; perceived benefits; technological readiness.